Staff Machine Learning Engineer

Prodege, LLC is a marketing and consumer insights platform that helps brands, marketers, and agencies acquire customers, increase revenue, and drive loyalty and product adoption. The Staff Machine Learning Engineer will build, deploy, operate, and improve production machine learning systems for ranking, recommendations, personalization, rewards optimization, prediction, and experimentation while partnering with cross-functional teams and mentoring engineers.

Responsibilities:

• Design, build, and operate production machine learning systems from development through deployment
• Production models supporting ranking, recommendations, personalization, rewards optimization, ROAS/LTV prediction, and offer optimization
• Feature engineering, model training pipelines, online inference, experimentation, monitoring, and continuous improvement
• Reliable production ML practices including testing, observability, retraining, and model health
• Technical leadership through code reviews, collaboration, and mentoring less experienced engineers
• Cross-functional partnerships with Product, Data Engineering, Analytics, and Business stakeholders to solve high-impact problems
• Design, build, deploy, and maintain production machine learning systems
• Develop scalable ML solutions across ranking, recommendation, personalization, rewards optimization, ROAS/LTV prediction, and experimentation
• Improve feature engineering, model performance, inference latency, and operational reliability
• Design and analyze offline evaluations and A/B experiments to validate business impact
• Partner with Data Engineering to build reliable data pipelines and feature sets for ML
• Contribute to MLOps practices including deployment, monitoring, retraining, and model lifecycle management
• Review code, mentor teammates, and help raise engineering quality across the ML organization
• Leverage AI-assisted development to accelerate research, prototyping, debugging, documentation, and experimentation

Requirements:

• • 6+ years of experience in Machine Learning Engineering, Software Engineering, MLOps, or related technical fields
• • 3+ years building, deploying, and operating production machine learning systems
• • Strong experience building production recommendation, ranking, personalization, optimization, or prediction systems
• • Experience working in AdTech, MarTech, Growth, Consumer Products, Marketplace platforms, or adjacent domains
• • Strong understanding of:
  • Feature engineering
  • Offline and online inference
  • Experimentation and A/B testing
  • Model serving
  • Monitoring and retraining
  • MLOps best practices
• • Experience partnering closely with Product, Engineering, and Data teams to deliver measurable business outcomes
• • Strong software engineering fundamentals with excellent coding skills
• • Comfort operating in ambiguous environments while independently driving technical solutions
• • Demonstrated ability to mentor engineers and influence technical decisions across teams
• • Experience with ROAS optimization, bidding systems, rewards platforms, or monetization models
• • Experience with streaming or near-real-time ML systems
• • Experience with recommendation engines or personalization at scale
• • Experience using feature stores or shared ML infrastructure
• • Experience with causal inference, uplift modeling, or counterfactual reasoning
• • Master's degree or PhD in Machine Learning, AI, Computer Science, or a quantitative discipline
• • Experience using AI-assisted development tools in software engineering workflows